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kb_list

List all knowledge bases on the hub with their subject, document count, and pending proposals. Optionally include pending concerns to avoid submitting duplicates.

Instructions

Liste les bases de connaissance disponibles sur ce hub, avec leur objet, leur nombre de documents et le nombre de propositions en attente. Aucune base n'est actuellement enregistrée.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
include_pending_concernsNoAjoute, pour chaque base, la liste (id, type, concerns) des propositions en attente. Utile pour éviter de soumettre un doublon, et pour inventorier à moindre coût.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses what the tool returns but does not state that it is read-only, nor any limits, errors, or side effects. More critically, the sentence 'Aucune base n'est actuellement enregistrée' asserts a current state that is not a permanent behavioral trait and may become false, misleading the agent into expecting an empty list. This adds confusion rather than transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with the core purpose. However, the second sentence is a dynamic state claim that is not a stable fact, adding noise and potentially misleading the agent. This detracts from conciseness because the information is not consistently true and distracts from the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one optional parameter and no output schema, the description explains the output fields sufficiently. The parameter is documented in the schema, so the agent can discover it. There is no mention of error handling, but for a read-only list operation, this is not critical. The description covers the essential outcome and structure adequately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100% and includes a detailed description of the single parameter 'include_pending_concerns' explaining its purpose and utility. The tool description adds no parameter information, but the baseline of 3 applies because the schema already covers semantics effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists knowledge bases on the hub, specifying the returned fields (object, document count, pending proposals). This distinguishes it from siblings like kb_search (search) and kb_read (read a specific base). The core purpose is unambiguous, though the second sentence introduces confusion about current data state.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this is for getting an overview of all bases, but it does not explicitly mention when to use it versus alternatives like kb_search or kb_propose. There are no exclusions or alternative routing, leaving the agent to infer usage from the tool name and sibling context. This is implied usage, not explicit guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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